Expanding from Basic Towards Systems Pharmacodynamic Models for 
Methylprednisolone

Vivaswath S. Ayyar, Ph.D., Research Assistant Professor of Pharmaceutical 
Sciences, University at Buffalo, NY and PK/PD Scientist, Janssen 
BioTherapeutics, Spring House, PA

Thursday May 23, 2019, 12:00 to 1:00 pm EDT

Register at 
https://register.gotowebinar.com/register/2512261322183894796?source=website

Abstract: Evolving upon foundational principles of classical pharmacology 
mostly applied to static systems, a diversity of basic 
pharmacokinetic/pharmacodynamic (PK/PD) models have emerged. Placing emphasis 
on parsimony, the basic "mechanism-based" models incorporate and relate plasma 
pharmacokinetics, receptor binding, and/or relevant homeostatic mechanisms 
controlling drug response.
Continued refinement of PK/PD models based upon a progressively deeper 
mechanistic appreciation of physiologically-based PK, pharmacology of 
drug-target interactions, and systems physiology from the molecular (genomic, 
proteomic, metabolomic) to cellular to whole body scales have laid the 
foundation for building mechanistic quantitative systems pharmacology (QSP) 
models. Previous research based on various animal, clinical, and theoretical 
studies with corticosteroids have provided ideas to broadly advance the fields 
of pharmacokinetics and pharmacodynamics.
Our recent work on modeling diverse aspects of corticosteroid systems 
pharmacology reflect the integration of basic pharmacodynamic models along with 
the assimilation of fundamental insights gained from many focused studies of 
corticosteroids. These models highlight the application of combined systems 
(experimental and modeling) approaches to decipher "horizontal" and "vertical" 
pharmacokinetic/ pharmacodynamic/ pharmacogenomic (PK/PD/PG) relationships of 
the synthetic corticosteroid, methylprednisolone, in relation to 1) circadian 
gene expression and inter-tissue responses, 2) biological signaling networks, 
and 3) sex differences, using systems pharmacology approaches supported with 
data from microarray and proteomics analysis, systemic physiological 
measurements, and/or more focused quantitation of mechanistic biomarker(s). The 
modeling strategies employed, major findings, and lessons learned from these 
studies are described.

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